Recognition of Characters of New-born Baby's Fingerprinting Using Machine Learning

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The ability to recognize fingerprints properly and quickly has been possible thanks to the development of machine learning (ML) techniques, which have revolutionized the biometric identification field. In this research work, we offer a machine-learning method for character recognition in newborn fingerprints. A collection of newborn fingerprint photos with known demographics (gender, age, and ethnicity) was gathered, and the images were pre-processed to improve contrast and reduce noise. Relevant information was extracted from the photos using feature extraction techniques, and machine learning (ML) algorithms like support vector machines (SVM), decision trees (DT), and neural networks (NN) were trained to identify the distinctive fingerprint traits of a newborn. The results of the study showed that the recommended method, which employs ML algorithms, can correctly recognize the characteristics of a newborn baby's fingerprints. Just a few of the metrics utilized to assess each ML model's performance in a hold-out validation situation were precision, recall, and F1 score. The decision tree achieved an 89% success rate, the neural network achieved 94% success rate, and the SVM algorithm achieved the success rate of 92%. These findings suggest that ML algorithms can quickly and accurately recognize the characters in a newborn baby's fingerprints. The suggested approach has numerous uses in security and healthcare systems where precise identification is essential. Accurate infant identification is essential in the healthcare industry to guarantee proper medical care and avoid medical errors. Access control in security systems can be implemented with fingerprint recognition. This study advances the use of machine learning (ML) to recognize characters in newborn baby fingerprints more accurately and efficiently. The results could have a big impact on security and healthcare systems. The suggested technique, which makes use of machine learning techniques, can quickly and precisely identify the characters in a newborn baby's fingerprints. This study adds to the development of more precise and effective techniques for the recognition of newborn baby fingerprint characters, highlighting the potential uses of machine learning in healthcare and security systems.&nbsp;